Paper Info
Title
An Enhanced MSER Based Method for Detecting Text in License Plates.
Abstract
In this paper, we propose a novel method for detecting license plates (LP) in images. The proposed algorithm is an extension of Maximally Stable Extremal Regions (MSER) for extracting candidate text region of LP. The approach is more robust to edge and more powerful thanks to its stability, and robustness against the changes of scale and illumination. We propose a novel method based on a bilateral filter as well as an adaptive dynamic threshold so as to improve the MSER results. Besides, we consider the outer tangent of circles intersection for filtering the region with the same orientation, and finally a character classifier based on geometrical and statistical constraints of character to eliminate false detection. Thus, our proposal consists of three steps namely, image preprocessing, candidate license plate character detection, and finally filtering and grouping to eliminate false detection. Experimental results showed that our approach results in significant improvement compared to another compared method. Indeed, the recall rate of our method is equal to 96% and the standard measure of quality F rate is equal to 97%.
Year
DOI
Venue
2018
10.1007/978-3-319-96292-4_36
Communications in Computer and Information Science
Keywords
Field
DocType
VLP detection,MSER region,Image text detection,License plate recognition,Component,Plate region extraction
Data mining,Pattern recognition,Computer science,Filter (signal processing),Robustness (computer science),Tangent,Maximally stable extremal regions,Preprocessor,Artificial intelligence,Bilateral filter,Classifier (linguistics),License
Conference
Volume
ISSN
Citations 
872
1865-0929
0
PageRank 
References 
Authors
0.34
9
3
Name
Order
Citations
PageRank
Mohamed Admi100.34
Sanaa El Fkihi2107.52
Rdouan Faizi3104.97